UTDSIDSIEventsDSI Meet Up - in collaboration with DMB on AI and Wearable Innovations for Digital Society

DSI Meet Up - in collaboration with DMB on AI and Wearable Innovations for Digital Society

Join us for this month's DSI Meet Up on November 26, focussing on AI and Wearable Innovations for Digital Society

This DSI-DMB-seminar explores cutting-edge research in deep learning for agricultural health and wearable technologies for indoor tracking and health diagnostics, highlighting their transformative impact on data management and the digital society.

Speakers and Abstracts

Dr. Rose Nakibuu
Lecturer, School of Computing and Informatics Technology, Makerere

Title: Application of Deep Learning in Agriculture: damage, variety and disease detection in Mangoes and Groundnuts

Objectives:

- Explore the use of deep learning techniques in detection of mango fruit damage, Groundnut seed variety and diseases

- Present findings from our ongoing research and outline future directions

Abstract:

Accurate detection of crop variety, damage and disease infestation in Mangoes and Groundnuts is pivotal as it directly affects both yield and trade worldwide. Timely identification of such damage and disease is critical to mitigating the spread of infestation and minimizing associated losses while understanding the how different crop varieties respond to damages and disease infections

This presentation will delve into our current research on utilizing deep learning for mango fruit damage, groundnut disease diagnosis as well as variety identification

More information about Dr. Rose Nakibuule you can find here.

Dr. Odongo Steven Eyobu
Lecturer, School of Computing and Informatics Technology, Makerere University, Uganda. Lead, Computational Intelligence at the GDCI lab, Makerere University.

Title: Enhancing Assistive Living with Intelligent Systems

Interest Area: Indoor Localization, Activity Recognition, Health Diagnostics

Keywords: Mobile Devices, Wearables, Datasets

Objectives:

- Explore the benefits of wearable technologies in improving indoor tracking and activity recognition efficiency

- Address challenges and considerations in evaluating and implementing these technologies

- Present findings from our ongoing research and outline future directions

Abstract:

The rapid advancement of wearable and sensor technologies has paved the way for significant progress in user tracking, assistive living, and health monitoring. Wireless technologies have emerged as the preferred method to meet the rigorous demands associated with these applications.

This presentation will delve into our current research on utilizing Pedestrian Dead Reckoning (PDR) for indoor user tracking and activity recognition leveraging IMU sensor data. Additionally, insights will be shared regarding our work in intelligent health diagnostics for Maternal health care and Lower Respiratory tract disease prediction, both, using chatbots at the GDCI lab, Makerere University.

More information on Dr. Odongo Steven Eyobu you can find here and here.

registration

Interested in joining this DSI Meet Up? Please ensure you register in advance. We hope to see you there!

DSI Meet Up - in collaboration with DMB on AI and Wearable Innovations for Digital Society
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